Competitor identification has been discussed for decades, and various frameworks and processes have been developed to analyze rival companies. However, the advanced development of information technologies has altered the paradigm of competition. Today, it is indispensable for companies to identify potential competitors across different industries in advance. This study constructed a case study regarding Eastman Kodak Company and Apple Inc., combining text mining technologies with patent documents, to investigate the correlation between patents and whether patent similarity can be an indicator of latent competition. With patents from United States Patent and Trademark Office (USPTO), this study developed different solutions and verified them with early patents. The results indicate that the similarity score between patents is an effective indicator to estimate the relation between cross-industries companies, and the provided framework is feasible for identifying latent rivals.
Lin, Yi-ling; Sung, Huang-Chih; Yang, Wei-An; and Cheng, Chun-Yen, "Identifying Future Competitors with Patent Text Mining" (2022). PACIS 2022 Proceedings. 116.
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